Air-ground Cooperative Inspection Algorithm Based on Wireless Power Transfer and Multi-level Edge Offloading

被引：0
|
作者：
Chen Z. [1 ,2 ]
Yang J. [1 ]
Xiao N. [1 ]
Tian X. [3 ]
机构：
[1] Department of Electronics and Communication Engineering, North China Electric Power University, Hebei Province, Baoding
[2] Hebei Provincial Key Laboratory of Electric Power Internet of Things Technology, North China Electric Power University, Hebei Province, Baoding
[3] Tangshan Power Supply Company of State Grid Jibei Electric Power Co., Ltd., Hebei Province, Tangshan
来源：
Dianwang Jishu/Power System Technology | 2022年 / 46卷 / 10期
基金：
中国国家自然科学基金;
关键词：
intelligent inspection; mobile edge computing; Q-learning; resource optimization; wireless power transfer;
D O I：
10.13335/j.1000-3673.pst.2021.1644
中图分类号：
学科分类号：
摘要：
The usage of intelligent robots and drones could make equipment inspections more efficient and automatic. Ground robots have several advantages in close inspections on the ground and indoors. UAVs are flexible, with greater inspection range and efficiency, but there are restrictions such as energy supply. In order to give full play to superiority of air-ground joint inspection, this paper proposed a ground-based robot and UAV cooperative inspection algorithm, which based on wireless power transfer and multi-level edge unloading. Firstly, in connection with the typical substation scenario, calculation methods of energy consumption, rate and time delay of all levels of equipment in local calculation and unloading were proposed, and a multi-level task unloading model under the conditions of wireless power transfer and UAV relay was established. Then, this study taking the requirements of time delay and energy consumption into account, the optimization inspection problem was described as a Markov decision process, and an optimal task offloading algorithm based on Q-Learning was proposed. The simulation comparison verified the effectiveness and reliability of this algorithm, and the flexible unloading algorithm could maximize the overall performance of the system. © 2022 Power System Technology Press. All rights reserved.
引用
收藏
页码：3961 / 3969
页数：8
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